Computer systems now use a variety of input devices, including keyboards, mice, graphics tablets, light pens, touch sensitive screens. Recently, computer systems used in virtual reality systems and other complex systems (such as remote control robotics and weapons systems) have adopted additional input devices, including head-mounted sensors, infrared eye-lens sensors, and data gloves. These devices sense movement of the body through a variety of sensors, and send signals to the computer system to indicate the position of the body.
Data gloves have been proposed for use as input devices for computer systems. For example, the data glove developed by VPL Research, Inc., and illustrated in, Interfaces for Advanced Computing, Scientific American (October 1987) (And also the subject Zimmerman, Computer Data Entry and Manipulation Apparatus and Method, U.S. Pat. No. 4,988,981 (Jan. 29, 1991)) used fiber-optic flexion sensors to determine how much each finger on the glove is bent. The glove also used an ultrasonic position sensor and a mercury switch orientation sensor mounted on the back-hand surface of the glove to determine the location of the glove and send this information to the computer used with the glove.
Grimes, Digital Data Entry Glove Interface Device, U.S. Pat. No. 4,414,537 (Nov. 8, 1983) proposed a data glove designed to replace a computer keyboard. This glove used flex sensors and electrical contacts on the fingertips to determine static positions representing the characters of the alphabet. Kramer, Force Feedback and textures Simulating Interface Device, U.S. Pat. No. 5,184,319 (Feb. 2, 1993) shows a data glove using strain gauges attached to the fingers of the to sense the bend of fingers, and to transmit this information to a computer. Robinson, Video Control Gloves, U.S. Pat. No. 4,613,139 (Sep. 23, 1986) proposes use of a glove with contacts on the fingertips to be used as an input device for a video game.
The data gloves can be used in virtual reality environments or "worlds" with varying degrees of complexity. The are potentially useful for selection of virtual object in a virtual environment. By correlating the position of the hand and the shape of the hand as sensed by the sensors on the glove to the position, shape and assigned function of a virtual object within the virtual environment, the host computer can interpret hand positions as instructions to manipulate the objects. More simply, by sensing the shape of the hand, the host computer can interpret the input as commands to the host system. For example, the Zimmerman device was designed to correlate contact between the thumb and other fingers to letters of the alphabet, and gestures are interpreted as commands to enter letters into a computer word processing file. In the Robinson device, contact between the thumb and the fingers were to be interpreted by the host computer as instructions in a video game program.
In flex sensing gloves, the glove can sense whether the glove is bent or not, but cannot accurately sense the degree of bend. In general, glove flexion of the fingers has not been used for rate control because the sensing is too difficult and the feedback to the user is not sufficiently accurate for efficient control. Virtual environment parameters such as the speed of flying have not generally been tied to the degree of the bend of a finger, and the firmness of grasp is not tied to how tightly a fist is made.
The electronics required for use of the touch sensing gloves is relatively straightforward when compared with the electronics required for measurement and calibration of a number of strain gauges attached to the back of the hand or measuring the angles in an mechanical or fiberoptic exoskeleton attached to the hand.
One shortcoming of flexion gloves is the absence of easily understood feedback to the operator of the glove. The degree of bend, in systems that are sensitive enough to use that information, may be misinterpreted by the system, or the system may be or become miscalibrated, so that the bend interpreted by the computer is significantly different than the actual bend accomplished by the operator. Deviation between the actual bend and the interpretation by the computer can be difficult to detect. Contact gloves overcome this shortcoming, in that they provide positive feedback to the operator because the operator can feel the contact between the thumb and fingers. After operating the system for a while, the operator will expect the host computer to react in known ways to the contact which the operator can feel. Any deviation should be easy to perceive. The disadvantage of prior art contact gloves, however, is that they cannot interpret multiple simultaneous gestures, or gestures that involve fingers other than a chosen signal finger (usually the thumb), and they do not account for cross hand contact.